To compare their performance on high dimensional data, several regression methods are applied to data sets in which the number of exploratory variables greatly exceeds the sampl...
Abstract Partial least squares (PLS) regression ( a.k.a. projection on latent structures) is a recent technique that combines features from and generalizes principal component a...
Miilticollinesrity among the columns of regressor variables is known to cause severe distortion of the least squares estimates of the parameters in a multiple linear regression ...
Structural equation modeling (SEM) has become a quasi-standard in marketing and management research when it comes to analyzing the cause-effect relations between latent construc...
Abstract In this paper a general algorithm is provided for maximum likelihood fitting of deterministic models subject to Gaussian‐distributed residual variation (including any t...
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